On-line dynamic security assessment of isolated networks integrating large wind power production

Detalhes bibliográficos
Autor(a) principal: João Abel Peças Lopes
Data de Publicação: 1999
Outros Autores: N. Hatziargyriou, Maria Helena Osório Pestana de Vasconcelos, E. Karapidakis, José Nuno Moura Marques Fidalgo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/19484
Resumo: The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed. The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed.
id RCAP_c304d3f13870abd5c2c757fa26fd5b21
oai_identifier_str oai:repositorio-aberto.up.pt:10216/19484
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling On-line dynamic security assessment of isolated networks integrating large wind power productionEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringThe paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed. The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed.19991999-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/19484engJoão Abel Peças LopesN. HatziargyriouMaria Helena Osório Pestana de VasconcelosE. KarapidakisJosé Nuno Moura Marques Fidalgoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T15:47:56Zoai:repositorio-aberto.up.pt:10216/19484Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:32:28.093722Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv On-line dynamic security assessment of isolated networks integrating large wind power production
title On-line dynamic security assessment of isolated networks integrating large wind power production
spellingShingle On-line dynamic security assessment of isolated networks integrating large wind power production
João Abel Peças Lopes
Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
title_short On-line dynamic security assessment of isolated networks integrating large wind power production
title_full On-line dynamic security assessment of isolated networks integrating large wind power production
title_fullStr On-line dynamic security assessment of isolated networks integrating large wind power production
title_full_unstemmed On-line dynamic security assessment of isolated networks integrating large wind power production
title_sort On-line dynamic security assessment of isolated networks integrating large wind power production
author João Abel Peças Lopes
author_facet João Abel Peças Lopes
N. Hatziargyriou
Maria Helena Osório Pestana de Vasconcelos
E. Karapidakis
José Nuno Moura Marques Fidalgo
author_role author
author2 N. Hatziargyriou
Maria Helena Osório Pestana de Vasconcelos
E. Karapidakis
José Nuno Moura Marques Fidalgo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv João Abel Peças Lopes
N. Hatziargyriou
Maria Helena Osório Pestana de Vasconcelos
E. Karapidakis
José Nuno Moura Marques Fidalgo
dc.subject.por.fl_str_mv Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
topic Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
description The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed. The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed.
publishDate 1999
dc.date.none.fl_str_mv 1999
1999-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/19484
url https://hdl.handle.net/10216/19484
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799136233898639360

Registros relacionados